Read level grouping algorithms for increased flash performance

ABSTRACT

A plurality of flash memory wordlines of a flash storage device are divided into a plurality of wordline groups based on read error counts associated with the wordlines and a plurality of read level offsets. Each wordline group is associated with one of a plurality of read level offsets determined while dividing the plurality of flash memory wordlines, and associations between the plurality of read level offsets and the plurality of wordline groups are stored for use in connection with read levels to read the flash memory wordlines of the respective wordline groups.

BACKGROUND

The present disclosure relates to the retrieval of information fromflash memory devices, such as solid-state drives (SSDs). Lower pricedSolid State Drives (SSD) are typically manufactured using multi-levelcell (MLC) flash memory for increased data capacity, but MLC memorydevices are sometimes less reliable than single-level cell (SLC) flashmemory. Consumer SSD manufacturers have mitigated such problems byemploying certain wear-leveling algorithms. Even with the increased datacapacity of MLC flash memory, using MLC flash memory in enterpriseapplications becomes more expensive due to increased (wear causing)stresses required to read, program and erase the flash memory, causing agradual degradation in endurance.

SUMMARY

The subject technology relates to a computer-implemented method ofreading a plurality of flash memory cells in a storage device. Accordingto various aspects, the method may include, dividing a plurality offlash memory wordlines of a flash storage device into a plurality ofwordline groups based on read error counts associated with the wordlinesand a plurality of read level offsets, associating each wordline groupbeing associated with one of a plurality of normalized read leveloffsets, each read level offset being normalized for a best possibleerror rate resulting from using the offset with a read level to read thewordlines of the associated wordline group determined while dividing theplurality of flash memory wordlines, and storing associations betweenthe plurality of normalized read level offsets and the plurality ofwordline groups for use in connection with the read levels in to readingthe flash memory cells during operation of the storage device wordlinesof the respective wordline groups.

In various aspects, a method may comprise dividing a plurality of flashmemory wordlines into a plurality of wordline group offset pairs, eachpair comprising an offset voltage for a group of consecutive wordlinesin a flash memory block, and storing the plurality of wordline groupoffset pairs for use in connection with a read level in reading thememory cells during operation of the storage device.

In various aspects, a data storage system comprises a plurality of flashmemory devices, each flash memory device comprising a plurality of flashmemory blocks, and a controller coupled to the plurality of flash memorydevices. The controller may be configured to store a plurality ofwordline group offset pairs for use in connection with a read levelvoltage in reading flash memory cells during a read operation, thewordline group offset pairs being formed from a division of a pluralityof flash memory wordlines, wherein each pair comprises an offset voltagefor a group of consecutive wordlines in a flash memory block.

It is understood that other configurations of the present disclosurewill become readily apparent to those skilled in the art from thefollowing detailed description, wherein various configurations of thepresent disclosure are shown and described by way of illustration. Aswill be realized, the present disclosure is capable of other anddifferent configurations and its several details are capable ofmodification in various other respects, all without departing from thescope of the present disclosure. Accordingly, the drawings and detaileddescription are to be regarded as illustrative in nature and not asrestrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an example graph diagram of four possible cell thresholdvoltage (V_(T)) distributions and complimentary read levels for a groupof memory cells in a multi-level cell (MLC) flash memory.

FIG. 2A depicts an example probability distribution for a leastsignificant bit (LSB) page using multiple read levels.

FIG. 2B depicts an example probability distribution for a mostsignificant bit (MSB) page of MLC flash memory using multiple readlevels.

FIG. 3 depicts example optimal read level voltage variations formultiple wordlines of a memory block.

FIG. 4 depicts an example table of error counts for an example range ofread level offset values for multiple wordlines.

FIGS. 5A to 5C depict charts of example optimal read level offsets forcycled memory blocks.

FIG. 6 depicts a block diagram of an example algorithm for generatingoffset wordline groups.

FIG. 7 depicts a flow diagram of a first example process for generatingoffset wordline groups.

FIG. 8 depicts a flow diagram of a second example process for generatingoffset wordline groups.

FIG. 9 depicts an example flash memory channel modeled as a discretememory-less channel (DMC) with binary inputs and K-ary outputs.

FIG. 10A to 10C depict example linear interpolation graphs forcalibrating example read levels and/or read level offsets.

FIGS. 10D to 10F depict example linear interpolation graphs forre-calibrating example read levels and/or read level offsets.

FIGS. 11A and 11B depict example read level optimization modes.

FIG. 12 depicts a flow diagram of an example process for calibratingread levels for reading a plurality of memory cells in a storage device.

FIG. 13 depicts a flow diagram of an example process for calibratingread levels to recover data.

FIG. 14 depicts a flow diagram of an example process for regenerating aplurality of optimal offset wordline groups based on regenerating andreindexing a table of error counts.

FIG. 15 is a block diagram depicting components of an example datastorage system.

DETAILED DESCRIPTION

The detailed description set forth below is intended as a description ofvarious configurations of the present disclosure and is not intended torepresent the only configurations in which the present disclosure may bepracticed. The appended drawings are incorporated herein and constitutea part of the detailed description. The detailed description includesspecific details for the purpose of providing a thorough understandingof the present disclosure. However, it will be apparent that the presentdisclosure may be practiced without these specific details. In someinstances, structures and components are shown in block diagram form inorder to avoid obscuring the concepts of the present disclosure. Likecomponents are labeled with identical element numbers for ease ofunderstanding.

In a flash memory device, for example, with NAND architecture, memorycells are grouped in strings, with each string consisting of a set oftransistors connected in series between a drain-select transistor(connected to a respective bit line of a memory block) and asource-select transistor (connected to a reference voltage distributionline). Each memory cell includes a floating-gate MOS transistor. Whenprogramming a memory cell, electrons are injected into the floatinggate, for example, by means of Fowler-Nordheim (F-N) Tunneling and/orhot-electron injection. The non-volatility of the memory cell is due tothe electrons maintained within the floating gate. Bits are stored bytrapping charge on the floating gate (an electrically isolatedconductor) which stores a logic value defined by its threshold voltage(voltage required to conduct the cell) which is commensurate with theelectric charge stored. When a memory cell is erased, the electrons inthe cell's floating gate are pulled off by quantum tunneling (a tunnelcurrent) from the floating gate to, for example, the source and/orsubstrate.

As a flash memory is cycled (that is, programmed and erased repeatedly),its physical qualities change. For example, the repeated placement andremoval of electrons on the floating gate during programming and eraseoperations, respectively, causes some excess electrons to be trapped inthe floating gate. Also, when one or multiple memory cells areprogrammed, adjacent cells may experience an unexpected and undesiredcharge injection to their floating gates, thus leading to corruption ofdata stored therein. For instance, electrons may leak into neighboringcells after prolonged stress due to the voltages at the gates ofneighboring cells. The threshold voltages of these memory cells mayeventually take values that are different (higher or lower) thanexpected values, causing errors when the data is read. Generally, thedamage done becomes a function of the field strength (e.g., voltage) andduration; that is, programming the flash memory to high thresholdvoltage conditions increases the rate of damage arising from bothprogram and erase processes because it requires longer duration and/orhigher applied fields.

In various implementations, memory cells are arranged on a wafer in anarray of columns (bitlines) and rows (wordlines). The address of amemory cell represents the intersection of a bitline and wordlinecorresponding to (e.g., indexing) the memory cell. Flash memory mayfurther be composed of blocks, with each block divided into pages. Insome implementations of MLC memory, every row of flash memory cells iscomposed of 2 pages: a least significant bit (LSB) page and a mostsignificant bit (MSB) page. If a block has 128 pages then it may have 64rows of cells, with each row having two pages. Each row of flash memorycells may behave differently in their ability to accurately store data,because when cells are physically together in a die they are subject tovariations in voltages and resistances, and other characteristics thatmay have resulted from the manufacturing process.

In NAND architecture, it has been found that the problem of degradationis especially problematic because each transistor in the string of thecells being read (e.g., at a bitline) receives an elevated voltagestress, even though less than all of the cells of that string (e.g., ata location in the bitline corresponding to a designated wordline) may beread at any one time. Due to degradation, when programmed, the cells ofsome rows (wordlines) are further from their expected values (e.g., anexpected voltage measured at a corresponding bitline) than others. Ithas been observed that these variations can be associated withindividual wordlines. Accordingly, the subject technology characterizesthese variations as a measurable value, and provides a mechanism tocompensate for the variations at runtime. For example, if cell voltagesin a wordline are found to shift (e.g., as a result of acharacterization process) then a bias (e.g., an offset voltage) may beintroduced during the program or subsequent read operation to correctthe programmed voltage or read value. In this manner, the non-linearityof actual programming values between cells in different wordlines may bereduced, thereby reducing errors when reading the cells.

The same bias, however, may not be suitable for correcting read-relatederrors uniformly throughout a particular block or die. Additionally,storing bias values for each wordline or block can quickly consumememory useful for storage and may be become unmanageable and/or impedeperformance by requiring numerous lookups to apply the correct bias withevery read operation. Accordingly, the subject technology provides amechanism for determining and associating bias values with groups ofwordlines, with the bias values optimized for the lowest possible readerror rate for reading the wordlines within a group. The subjecttechnology further provides a mechanism for optimizing the bias valuesover the lifetime of the memory cells. In this manner, the bias valuesmay be efficiently stored and recalled, and corrected as needed, therebyimproving the reliability and endurance of the overall flash memory cellarchitecture, making the flash memory suitable for enterpriseapplications.

FIG. 1 is an example graph diagram of four possible cell thresholdvoltage (V_(T)) distributions (401, 410, 420, and 430) and read levels(L0, L1 and L2 thresholds) for a group of memory cells in a multi-levelcell (MLC) flash memory, according to aspects of the subject technology.MLC NAND flash memory provides for more than one bit per cell bychoosing between multiple levels of electrical charge (read level) toapply to the floating gates of its cells to achieve multiple states ofconductivity, each occurring at a different voltage threshold V_(T). Asdepicted in FIG. 1, a MLC NAND cell is capable of storing one of fourstates (levels of charge) per cell, yielding two logical bits ofinformation per cell: the Most Significant Bit (MSB) and LeastSignificant Bit (LSB). These two bits may make up corresponding MSB andLSB pages of a memory block.

FIG. 1 depicts probability density distribution curves 400 for a groupof memory cells (e.g., in a block) programmed to data levels L0, L1, L2,and L3. The distributions 401, 410, 420, and 430 correspond to theprobability density distribution curves for L0, L1, L2, and L3 datalevels, respectively. Each data level is separated by a respectivethreshold voltage level. In the depicted example, the threshold voltagelevels are identified as L0 threshold, L1 threshold, and L2 threshold.The threshold voltage levels are used by a threshold detector (e.g.,within the flash memory) as “read levels” to determine, for example, ifa read signal should be read as being in distribution 401, 410, 420, or430. The four cell distributions 401, 410, 420, and 430 of FIG. 1 may beobtained from lab data.

To ensure that all cells in a distribution will conduct, a read levelvoltage greater than the highest cell voltage in the distribution isapplied. In various examples described herein, a first read level RL1corresponds to the L0 threshold voltage, a second read level RL2corresponds to the L1 threshold voltage, and a third read level RL3corresponds to the L2 threshold voltage. In this regard, RL1 voltagewill cause cells in the L0 distribution to conduct, RL2 voltage willcause cells in the L1 and L0 distributions to conduct, RL3 voltage willcause cells in the L2, L1, and L0 distributions to conduct, and so on.Where, as depicted by FIG. 1, only four states are available, RL3voltage will not cause any cells in L3 distribution to conduct.Generally, for N distributions there will be N−1 read levels. In thedepicted example, there are four distributions (states) and three readlevels. However, it is understood that there may be eight, sixteen, ormore distributions without departing from the scope of the subjecttechnology.

FIG. 2A depicts an example probability distribution for a LSB page usingmultiple read levels, according to aspects of the subject technology. Inthe depicted example, a first read level 202 (“RL2”) is used in a firstread of a LSB page to determine putative program levels for the memorycells of the LSB page. To determine a probability that the memory cellswere actually programmed to the observed putative program levels,multiple “soft” reads below and/or above read level 202 may beinitiated.

In the depicted example, the memory cells are read using a second readlevel 204 below the first read level 202 and a third read level 206above the first read level 202. A first program region β₁ includes oneor more cells having a programmed value between the first read level 202and the second read level 204, and a second program region 132 comprisesone or more cells having a programmed value between the first read level202 and the third read level 206. The various regions between readlevels may be referred to herein as “bins.” In various aspects, aprobability value may be calculated for each bin based on how many ofthe memory cells are in the bin compared to one or more other bins. Aprobability may also be determined for a bin based on the size of anarea 208 (shown as a hatch pattern) under the distribution curve for thebin. Based on the probability, the reliability value is then generatedand assigned to each memory cell in the bin. As will be describedfurther, reliability values may include log-likelihood ratios.

FIG. 2B depicts an example probability distribution for a MSB page ofMLC flash memory using multiple read levels. According to aspects of thesubject technology, an initial read level 202 may be applied to one ormore memory cells to obtain a LSB value for each memory cell. In thedepicted example, read level 202 is chosen as the crossover locationbetween the distributions of coded bit 1 and coded bit 0 (as shown inFIG. 2A) to minimize an expected bit error rate (BER). Read levelschosen to minimize BER are called optimal read levels.

Based on the LSB value, a read level 208 may be determined for reading aputative program level for the MSB. Once read level 208 is determinedand the putative program level read using read level 208, multiplesubsequent soft reads (e.g., 210 and 212) around read level 208 may beinitiated to determine a probability that the MSB was actuallyprogrammed to the observed putative program level. Accordingly, theprogrammed value of each cell may be associated with a program region(bin) α₀, α₁, α₂, α₃, α₄, α₅, α₆, and α₇ corresponding to the level atwhich the cell was found to conduct or not conduct when the LSB and MSBreads, and associated soft reads, are applied.

FIG. 3 depicts example optimal read level voltage variations formultiple wordlines of a memory block, according to aspects of thesubject technology. A memory block may have up to (or more than) 64wordlines. Lab results have indicated that optimal read levels 302(e.g., RL1, RL2, or RL3) may vary from wordline to wordline. In thedepicted example, three read levels RL1, RL2, and RL3 are optimally setat their respective values to read memory cells in probability densitydistribution curves 304 corresponding to data levels L0, L1, L2, and L3.However, the values or voltages of these read levels 302 are shown tochange with respect to each wordline. For example, read levels 306 forwordline 1 are shifted to the right with respect to a reference point308, thereby exhibiting a slightly increase value, while read levels 310for wordline 64 is shifted left of reference point 308 having a slightlydecreased value. As will be described further, each of these shifts involtages for each read level may be represented as bias values, or readlevel offsets, from a respective primary read level voltage.

FIG. 4 depicts an example table of error counts 400 for an example rangeof read level offset values for multiple wordlines, according to variousaspects of the subject technology. As explained above, the optimal readlevel used to read a particular state of memory cell may vary fromwordline to wordline, illustrating that each wordline may have a uniqueset of characteristics with respect to each other. The variations inoptimal read levels between wordlines may be shown by modifying aprimary read level by a particular bias, also referred to herein as“read level offset.” The read level offset may be different for eachwordline and/or each block and/or each memory die. In this regard,multiple offsets may be applied: one for each wordline, one for eachblock, and/or one for each memory die.

Each row of the table 400 is representative of a different wordline,while each column representative of a different read level offset value.Each wordline of a block may be represented in the table. The errorcounts listed in the example table are the number of errors producedwhen reading the corresponding wordline at the corresponding offsetvalue. The error counts may be indexed by wordline and read level offsetvalue. The read level offset values are represented in “ticks” from aprimary read level voltage. In some implementations every two ticks maybe the equivalent of 25 mV. Additionally, there may be a different tablefor each read level voltage. For example, the depicted table may be forRL1, while a different table provides error counts for reading the samewordlines with RL2, and a different table provides error counts forreading the same wordlines with RL3.

The table may be initially generated based on lab data. In at least oneexample, the table of error counts may be generated based on reading thewordlines of a memory block, with each wordline being read multipletimes using a selected read level voltage modified for each read by adifferent offset voltage. Accordingly, an error count is produced foreach offset voltage, and the table is generated for indexing the errorcounts by a wordline number and respective offset voltages.

FIGS. 5A to 5C depict charts of example optimal read level offsets forcycled memory blocks, according to various aspects of the subjecttechnology. As explained above, as memory cells are cycled they mayexperience some degradation. Accordingly, distributions L0, L1, L2,and/or L3 may drift or move from the expected values, and new optimalread levels are required to read the cells at their new values withminimal errors. In the depicted examples, optimal read level offsetvalues are charted for 128 wordlines (0-127) of a memory block forprimary read levels RL1, RL2, and RL3. FIG. 5A is representative ofexample reads of MSB pages using RL1, and depicts how read level offsetvalues may vary between 18 and 12 ticks before settling at 14 ticks forthe higher wordline numbers. FIG. SB is representative of example readsof LSB pages using RL2. FIG. 5B depicts how a greater offset (i.e., 18ticks) is required at lower wordline numbers (e.g., at the beginning ofa block) than at higher wordline numbers (e.g., at the end of a block).The read level offset to apply to RL2 is seen to generally decline invalue, from 18 ticks for wordline 0, to 10 ticks for wordline 120, andthen finally to 4 ticks at wordline 127. FIG. 5C depicts a read leveloffset applied to RL3 declining linearly from 18 ticks for wordline 0 to−2 ticks at wordline 126, and then +2 ticks at wordline 127.

Determining Read Level Offset Groups for Use During Read Operations

FIG. 6 depicts a block diagram of an example algorithm for generatingoffset wordline groups, according to various aspects of the subjecttechnology. Algorithm 602 may be implemented as computer software (e.g.,instructions executing on a computing device), electronic hardware, orcombinations of both. Storing the offset values required to provideoptimal read levels for reading memory cells in, e.g., each of the 128wordlines using three (or more) different read levels would consume alarge amount of memory space. Accordingly, the subject technologyimplements a read level profiling algorithm 602 that reduces the amountof offset values (or read levels) required to be stored while providinga close to optimum bit error rate reduction in memory read operations.Read level profiling algorithm 602 reduces the number of stored readlevel offsets while not degrading the bit error rates produced bycorresponding read operations that could increase hard or soft decodingfailures.

The example read level grouping algorithm 602 takes as inputs initialboundary conditions, e.g., in the form of an initial division ofwordlines for a block, a desired number of wordline groups, and thepreviously described table of error counts 400. Each division ofwordlines defined by the boundary conditions forms a set of candidate(input) wordline groups, each made up of consecutive wordline addresses.For example, the initial boundary conditions may designate fourcandidate groups, with group 1 as wordlines 0-31, group 2 as wordlines32-63, group 3, as wordlines 64-95, and group 4 as wordlines 96-127.These candidate groups set up initial boundary conditions that algorithm602 will use to analyze error rates and to ultimately generate optimalboundary conditions for forming optimal (output) offset wordline groupsfor use in read operations during operation of a storage device.

Example algorithm 602 takes table 400 of FIG. 4 and the initial boundaryconditions and outputs optimal offset wordline groups. Each optimaloffset wordline group output by algorithm 602 includes a consecutiveportion of the total wordlines input as part of the initial conditions(e.g., 128 wordlines). The boundaries of the optimal offset wordlinegroups output by algorithm 602 may or may not be the same as the initialboundary conditions, and in many cases will be different. Each optimaloffset wordline group includes consecutively grouped wordlines pairedwith a corresponding optimal offset voltage for the group. The groupsmay be consecutively ordered with respect to their wordlines.

In various implementations, each pairing of each optimal offset wordlinegroup to each respective optimal offset voltage is automaticallyselected by the algorithm for an overall lowest possible error count forreading wordlines in each of the offset wordline groups, and the groupsas a whole. Generally, the set of optimal offset wordline groupsgenerated by algorithm 602 are generated, at least in part, based oniteratively indexing table 400 based on wordline location and offsetvalues for each initial set of wordline groups to determine a best fit,or normalized, error count for each output group. Accordingly, readlevel grouping algorithm 602 outputs optimal offset wordline groups(e.g., as boundaries for each group) and the optimal read level offsets(or read levels) for each group offering the least bit error ratedegradation, e.g., based on the input table 400.

FIG. 7 depicts a flow diagram of a first example process 700 forgenerating offset wordline groups, according to various aspects of thesubject technology. For explanatory purposes, the various blocks ofexample process 700 are described herein with reference to thecomponents and/or processes described herein. One or more of the blocksof process 700 may be implemented, for example, by one or moreprocessors, including, for example, controller 1501 of FIG. 15 or one ormore components or processors of controller 1501. In someimplementations, one or more of the blocks may be implemented apart fromother blocks, and by one or more different processors or controllers.Further for explanatory purposes, the blocks of example process 700 aredescribed as occurring in serial, or linearly. However, multiple blocksof example process 700 may occur in parallel. In addition, the blocks ofexample process 700 need not be performed in the order shown and/or oneor more of the blocks of example process 700 need not be performed.

According to various implementations, one or more blocks of process 700are implemented by read level grouping algorithm 602. In this regard,the blocks of process 700, or subset thereof, may be executed for eachpossible read level used in a flash memory device. For example, theblocks of process 700 may be executed to generate optimal offsetwordline groups for RL1, RL2, and RL3 based on table 400 and inputboundary conditions. In various aspects, offset wordline groups ofdifferent sizes and/or having different offset value pairings may begenerated for each different read level. Additionally, the blocks ofprocess 700 may be executed to generate different groups for differentblocks, and or die. Process 700 may be implemented during configurationof a storage device, prior to or during operation.

Generally, for each initial boundary condition, process 700 executes anumber of iterative steps to automatically select optimal groupboundaries and corresponding optimal read level offsets for each groupthat offer the least increase in overall bit error rate compared tooptimal bit error rate, as determined by a corresponding input table400. For a number of candidate groups defined by the boundaryconditions, algorithm 602 may select two consecutive groups k and k+1,and beginning from the first element of the first group until the lastelement of the second group, consider all possible two consecutivedivisions.

In the depicted example, wordlines of a block are divided into candidategroups (702). In an example in which 128 wordlines are used, the blockmay be divided into four candidate groups, with group 1 as wordlines0-15, group 2 as wordlines 16-31, group 3, as wordlines 32-79, group 4as wordlines 80-127. The division of the block and resulting number ofcandidate groups may be selected based on lab data, or selected based ondividing the total number of wordlines of the block equally. Asdescribed previously, the division of groups may be represented asboundaries of the groups. Process 700 then selects a set of consecutivecandidate groups (704). For example, groups 1 and 2 may be selected,thereby forming a set of wordlines between 0 and 31. Permutations ofmultiple consecutive subgroups from the set are considered (706). Invarious examples herein, permutations of two subgroups are considered,however more subgroups may be considered. Since, in the given example,the subgroups are consecutive, and the wordlines within the groupconsecutive, the maximum number of permutation for n wordlines will ben−1 permutations. Permutations of an example set of wordlines spanning0-31 may include {[0, 1-31], [0-1, 2-31], [0-3, 4-31] . . . [0-30, 31]}.

Example process 700 is depicted as a min-average algorithm. That is, foreach possible permutation, the average error count is computed based ona corresponding error table, and then the subgroups within thepermutations are compared to select those with the fewest error counts.In this regard, error counts for each subgroup are computed using allavailable read level offsets based on the error count table 400, and theread level offsets that offer the least error counts for eachpermutation are determined. In the depicted example, process 700 beginsat (or selects) a first permutation (708) and then, for each subgroupwithin the permutation (710), finds the total error count correspondingto the subgroup for each offset value represented in the input table 400(712). The total error count may be found, e.g., by indexing table 400by a first offset value represented in table 400 and each wordlinewithin a first (i=1) subgroup to determine error counts for eachwordline within the subgroup, and then summing the determined errorcounts. Total error counts for the other offset values represented bytable 400 are determined in the same way, and the resulting sums oferror counts are compared to identify the offset value having the leasterror count for the subgroup. The identified offset value is thenselected and associated with the subgroup (714). The same process isapplied to the next subgroup of the permutation (715).

The foregoing process is repeated (716), restarting at block 708, untilan offset value is associated with each subgroup of each permutation,each subgroup also being associated with a total error countcorresponding to the associated offset value. Table 1, below, providesexample offset associations for three permutations of two subgroups.

TABLE 1 First Second First Second Subgroup Subgroup Subgroup SubgroupPermutation Offset Offset TEC TEC 0, 1-31 16 14 28640 16254321 0-1, 2-3118 16 63012 16222110 0-2, 3-31 18 18 104832 . . . 0-3, 4-31 18 18 . . .. . .

Once offset values are associated with each subgroup of eachpermutation, process 700 selects a permutation having the least totalerror count (718). The least total error count may be the total errorcount of both subgroups within the permutation, or the first or secondsubgroup, depending on the implementation of the algorithm used. Invarious examples, the total error count summed across all the wordlines(both subgroups) is used to compare permutations. Process 700 continuesby selecting the first subgroup and its corresponding offset of theselected permutation as an optimal pair (720).

In the depicted example, process 700 determines whether there are morecandidate input groups (722). If a next (e.g., third) candidate groupexists (e.g., wordlines 32-47 in the above example), the second(previously unselected) subgroup of the permutation identified at block718 is then selected and refactored into the algorithm with the nextcandidate group (724). In the above example, if the first subgroupincludes wordline boundaries of 0-22 generated based on a first andsecond candidate groups (having wordline boundaries of 0-31) then thesecond subgroup having wordlines 23-31 will be used in the next set ofcandidate groups together with the next subsequent candidate group inputinto the algorithm. Therefore, in the above example, the next set ofcandidate groups would include a candidate group having wordlines 23-31and a candidate group having wordlines 32-47. If a next candidate groupdoes not exist then the algorithm may select the second subgroup and itscorresponding offset of the permutation identified in block 718 as afinal optimal pair (726).

In some implementations, blocks 702 through 726 may be repeated untilthe output group boundaries do not change from one iteration to the nextiteration, or until an overall bit error rate measured for theconsecutive wordline subgroups does not change from one iteration to anext iteration, or a certain number of iterations is reached. Eachiteration may be run using the output boundary conditions produced atthe end of block 726. Randomization may also be introduced withinprocess 700. For example, permutations may be generated that includesubgroups that are not in any particular order. A first subgroup mayinclude wordlines 13-31 and a second subgroup may include wordlines0-12. As the optimal pairs are identified (or after the iterativeprocess has been completed), the optimal pairs are stored for use inreading the memory cells during operation of the storage device. Thestorage device may then, during a read operation, match the wordlinethat is the subject of the read operation to a group of an optimal pair,and use the offset of the optimal pair in reading the memory cells ofthe wordline.

While example process 700 is depicted as a min-average algorithm, othertypes of algorithms may be implemented. For example, a min-max algorithmmay be implemented. In this manner, block 712 may be modified to, foreach subgroup within the permutation (710), find the maximum error countof all wordlines in the subgroup for each offset value (712). The errorcounts may be found, e.g., by indexing table 400 by a first offset valueand comparing the error count indexed by the first offset value and eachwordline in the subgroup (e.g., wordlines 0, 1, 2, and 3 in the firstsubgroup of permutation {[0-3], [4-31]}). The maximum error counts foundfor each offset value are then compared, and the offset valuecorresponding to the minimum of all maximum error counts is thenselected and associated with the subgroup (714). The same process may beapplied to the next subgroup of the permutation. Before moving to thenext permutation, in block 715, the maximum of the minimum error countsselected for the subgroups (of the current permutation) are noted. Oncea maximum has been noted for each permutation, in block 718, thepermutation associated with the minimum of these values is thenselected. One benefit of process 700 implementing a min-max algorithmincludes keeping errors below a maximum capacity of the error correctioncoding used by the storage device to correct errors.

In certain aspects, the subject technology may include theimplementation of different blocks or steps than those discussed abovewith respect to example process 700. By utilizing previously selectedinitial boundary conditions and table 400, process 700 outputsboundaries for optimal offset wordline groups, including the optimalread levels for each group offering, e.g., the least bit error ratedegradation for each wordline in each group from optimal values in table400.

FIG. 8 depicts a flow diagram of a second example process 800 forgenerating offset wordline groups, according to various aspects of thesubject technology. For explanatory purposes, the various blocks ofexample process 800 are described herein with reference to thecomponents and/or processes described herein. The one or more of theblocks of process 800 may be implemented, for example, by one or moreprocessors, including, for example, flash memory controller 1501 of FIG.15 or one or more components or processors of controller 1501. In someimplementations, one or more of the blocks may be implemented apart fromother blocks, and by one or more different processors or controllers.Further for explanatory purposes, the blocks of example process 800 aredescribed as occurring in serial, or linearly. However, multiple blocksof example process 800 may occur in parallel. In addition, the blocks ofexample process 800 need not be performed in the order shown and/or oneor more of the blocks of example process 800 need not be performed.

According to various implementations, a portion of the blocks of process800 may be executed by algorithm 602. The blocks of process 800, orsubset thereof, may be executed for each possible read level used in aflash memory device. For example, the blocks of process 800 may beexecuted to generate optimal offset wordline groups for RL1, RL2, andRL3 based on table 400 and input boundary conditions. In variousaspects, offset wordline groups of different sizes and/or havingdifferent offset value pairings may be generated for each different readlevel. Additionally, the blocks of process 800 may be executed togenerate different groups for different blocks, and/or die. Process 800may be implemented during configuration of a storage device, prior to orduring operation.

In the depicted example, a flash memory device provides a read levelvoltage sufficient to read memory cells that are programmed to aprogramming level (802). For example, the read level voltage may bepre-programmed into a state machine of flash memory device by themanufacturer or the storage device controller. In some implementations,each memory cell is a multi-level flash memory cell configured to beprogrammed to one of four programming levels. For example, withreference to FIG. 2B, L0 and L3 programming levels may be associatedwith first bit values (e.g., representative of a binary value of a mostsignificant bit) and L1 and L2 programming levels may be associated withthe second bit values (e.g., representative of a binary value of a leastsignificant bit). As described previously, when voltage is applied to amemory cell at a particular read level (e.g., RL1, RL2, RL3)corresponding to the program level of the cell the cell will conductindicating the program level.

The system divides a plurality of flash memory wordlines of a flashstorage device into a plurality of wordline groups based on read errorcounts associated with the wordlines and a plurality of read leveloffsets (804). Each of the optimal wordline groups is made up ofconsecutively ordered wordlines of a memory block, with wordlines of afirst one of the groups preceding wordlines of a second one of thegroups. In this regard, each offset is chosen for a best error rateresulting from use of the offset with the read level voltage to read thewordlines of a corresponding wordline group. For example, respectivepermutations of consecutive wordline subgroups may be selected fromwithin a predetermined set of wordline candidate groups based on aminimum of total error counts associated with the respectivepermutations (e.g., blocks 708-720 of FIG. 7), and each of theconsecutive wordline subgroups may be associated with a read leveloffset corresponding to a minimum of error counts associated with aplurality of possible read level offsets.

With reference to FIG. 7, first and second consecutive wordline groupsmay be selected from the predetermined set of candidate wordline groups(704). As described previously, the candidate wordline groups may bebased on initial boundary conditions. A plurality of subgrouppermutations may then be provided for the selected first and secondconsecutive wordline groups (706), with each subgroup permutationcomprising multiple consecutive wordline subgroups of wordlines spanningthe first and second consecutive wordline groups. For each wordlinesubgroup of a respective subgroup permutation, a respective read leveloffset may be selected from the possible read level offsets such that,when used with the read level voltage to read the wordlines in thewordline subgroup, the respective read level offset generates the leastnumber of errors for the wordline subgroup (714). The plurality ofsubgroup permutations having a lowest total error count for consecutivewordline subgroups in the subgroup permutation may then be selected(718). Accordingly, the plurality of wordline groups may be based atleast in part on one or more read level offsets corresponding to theselected one of the plurality of subgroup permutations.

In some implementations, dividing the plurality of wordlines into theplurality of wordline groups includes selecting respective permutationsof consecutive wordline subgroups from within a set of wordlinecandidate groups (e.g., predetermined by the input boundary conditions)based on a minimum of maximum error counts associated with therespective permutations, with the consecutive wordline subgroups eachbeing associated with a read level offset corresponding to a minimum oferror counts associated with a plurality of possible read level offsets.As an example, for each wordline subgroup of a permutation, the systemmay determine an error count associated with reading wordlines (e.g., amaximum error count or an error count corresponding to a wordline in thegroup having the largest error count) in the wordline subgroup for eachpossible read level offset (used with the read level voltage to read thewordlines of the wordline subgroup). The read level offset correspondingto the minimum of the determined error counts may then be selected fromthe plurality of possible read level offsets for the wordline subgroup(see, e.g., 712). In this example, if there are two wordline subgroupsin the permutation then there may be two different (minimum) errorcounts that have been selected for the permutation (and twocorresponding read level offsets).

For each subgroup permutation, the maximum error count of the errorcounts associated with the wordline subgroups of the subgrouppermutation is noted. The subgroup permutation having the minimum of thedetermined maximum error counts is then selected (see, e.g., 718). Inthis manner, each wordline group is associated with one of a pluralityof read level offsets determined while dividing the plurality of flashmemory wordlines (806).

In one or more of the above implementations, each consecutive wordlinesubgroup of a respective permutation may be generated based on aninterleaving of consecutive wordlines within the predetermined set ofcandidate wordline groups. Interleaving may be used to introducerandomization. For example, a first wordline subgroup in a subgrouppermutation may include wordlines 14-31, followed by a second subgroupthat includes wordlines 0-13. In a subgroup permutation that includesthree subgroups (e.g., using three subgroups in block 706 of FIG. 7instead of two subgroups), a first wordline subgroup of the permutationmay include wordlines 4-6, a second wordline subgroup of the permutationmay include wordlines 0-3, and a third wordline subgroup of thepermutation may include wordlines 7-32.

Additionally, each respective read level offset may be generated (e.g.,using any of the implementations above) based on indexing a table oferror rates, with each error rate in the table being indexed based on arespective read level offset and a respective wordline. In this manner,the table may be indexed by a plurality of consecutive wordlines toidentify corresponding read level offsets having a lowest error rate foreach consecutive wordline, and determining a group of the consecutivewordlines that when associated with a single identified offset have aminimum possible error rate for the group of the consecutive wordlines.Accordingly, each wordline group is associated with one of a pluralityof read level offsets determined while dividing the plurality of flashmemory wordlines (806).

Once the wordline groups have been generated, the associations betweenthe plurality of read level offsets and the plurality of wordline groupsare stored for use in connection with read levels to read the flashmemory wordlines of the respective wordline groups (808). In thisregard, the foregoing process automatically selects optimal groupboundaries and corresponding optimal read level offsets for each groupthat offer the least increase in overall bit error rate compared tooptimal bit error rate.

Many of the above-described features of example processes 700 and 800and related features and applications, may be implemented as softwareprocesses that are specified as a set of instructions recorded on acomputer readable storage medium (also referred to as computer readablemedium). When these instructions are executed by one or more processingunit(s) (e.g., one or more processors, cores of processors, or otherprocessing units), they cause the processing unit(s) to perform theactions indicated in the instructions. Examples of computer readablemedia include, but are not limited to, CD-ROMs, flash drives, RAM chips,hard drives, EPROMs, etc. The computer readable media does not includecarrier waves and electronic signals passing wirelessly or over wiredconnections.

In low-density parity-check (LDPC) applications, a LLR may include thelogarithm of a ratio between the probability of a read bit being “0” or“1”. The LLR may span a predetermined range. For example, in someimplementations, an LLR may span the range −255 to +255. A positive LLRmay generally indicate that a signal read from the memory cell is likelyto be a 0-bit, and a negative LLR may generally indicate that a signalread from the memory cell is likely to be a 1-bit. The LLR may beassociated with the bit value read from the memory cell. A bitassociated with an LLR equal to 5 may be more likely to be a binary zerothan a bit having an assigned LLR equal to 1. A bit having an assignedLLR equal to 0 may be equally likely to be a binary one or zero.

If, at a certain read level, a 0-bit is read from a memory cell then apositive LLR may be assigned. If a 1-bit is read then a negative valuemay be assigned. In a multi-level memory cell having two bits, there aremultiple potential cell distribution levels (for example, L0, L1, L2,and L3). Distinguishing between a binary one and a binary zero in a readof a MSB may require determinations across multiple read levelboundaries. In the example of FIG. 1, distinguishing between a 0 and a 1requires determining whether the cell conducts within the middle twodistributions L1 and L2 (e.g., for a binary 0x), or in the enddistributions L0 and L3 (e.g., for a binary 1×). Accordingly, multipleread levels may be involved (for example, RL0 and RL2) to make thatdetermination.

Calibrating Read Levels and Read Level Offsets

FIG. 9 depicts an example flash memory channel 900 modeled as a discretememory-less channel (DMC) with binary inputs and K-ary outputs,according to aspects of the subject technology. In this example, theK-ary outputs correspond to K cell program regions (bins) that may beidentified with multiple reads. The model of channel 900 provides adefinition for a log-likelihood ratio (LLR). Using this model, the LLRmay be defined as:

$\begin{matrix}{{LLR}_{i} = {{\log \; \frac{p\left( {s_{i} = \left. 0 \middle| r_{i} \right.} \right)}{p\left( {s_{i} = \left. 1 \middle| r_{i} \right.} \right)}} = {\log \frac{{p\left( {\left. r_{i} \middle| s_{i} \right. = 0} \right)}{{p\left( {s_{i} = 0} \right)}/{p\left( r_{i} \right)}}}{{p\left( {\left. r_{i} \middle| s_{i} \right. = 1} \right)}{{p\left( {s_{i} = 1} \right)}/{p\left( r_{i} \right)}}}}}} & (1)\end{matrix}$

where s_(i) is the presumed (correct) input data bit that has beenstored for a particular cell and/or page, and where r_(i) is the softvalue corresponding to a bin that is read from the flash memory, andwhere p represents the (conditional) probability of being in the regionrepresented by r_(i) given that the bit value was programmed to s_(i).

In some implementations it may be assumed that all inputs are equallyprobable; as such the expression of Equation (1) becomes:

$\begin{matrix}{{LLR}_{i} = {\log \frac{p\left( {\left. r_{i} \middle| s_{i} \right. = 0} \right)}{p\left( {\left. r_{i} \middle| s_{i} \right. = 1} \right)}}} & (2)\end{matrix}$

With reference to FIG. 2A, if K=2 for a LSB page read, the K regions aredesignated as r_(i)ε{α₀,α₁} wherein the LLR for region α₁ of FIG. 2A isgiven by:

$\begin{matrix}{{{LLR}\left( \alpha_{1} \right)} = {\log \frac{p\left( {r_{i} = {\left. \alpha_{1} \middle| s_{i} \right. = 0}} \right)}{p\left( {r_{i} = {\left. \alpha_{1} \middle| s_{i} \right. = 1}} \right)}}} & (3)\end{matrix}$

With reference to FIG. 2B, in the case that K=8 for an MSB page read,the regions may be designated as:

r _(i)ε{α₀,α₁,α₂,α₃,α₄,α₅,α₆,α₇}  (4)

The read level may be set before each of N number of reads. A lookuptable may be used to determine how many read levels, and the values forthe read levels, based on how many bins are to be used in determiningLLR values for the memory cells. A flash memory device may be instructedto read the LSB or MSB page using the stored read levels. As describedpreviously, to create the bins, a first read level is used to determinea putative value of the cells and then multiple reads (e.g., a series ofreads) are performed to determine associated LLR values. In someaspects, read levels are determined by varying the first read level by apredetermined (e.g., stored) offset associated with a respective bin.This offset may be different than the offsets that are determined by thesubject technology.

Transitions in the read data are analyzed to determine which regioncontains the voltage threshold (V_(T)) of each memory cell. Accordingly,the first read level may be stored (e.g., temporarily), and a regiondetermined based on a binary value read from the memory cell, anddifferences between the first read level and subsequent read levelsinitiated by a memory controller. The read levels may or may not bechanged in a predetermined order. If the read levels are changed in aprescribed order, only the previous read level may be stored and thecell program region determined on each subsequent read. If all reads areperformed (e.g., at once), a lookup table may be used to determine thebins based on the received binary values. Once determined, a bin numberfor each cell program region may be determined. The LLR assigned to thebin may be applied to all cells falling within the bin. For each memorycell, the bin number is mapped to a LLR value in a lookup table.

In accordance with the foregoing, for a primary read level (e.g., RL1,RL2, or RL3), the number of bins will be equal to the total number ofreads, including soft reads, plus one. While FIGS. 2A and 2B depictthree reads for each primary read level, more reads are possible. For atotal of seven reads (including e.g., three soft reads on each side of aprimary read), a table may be generated for the LLR values that includes8 columns corresponding to the 8 bins. In this example an MSB page mayhave two rows, as shown in Table 2:

TABLE 2 0 1 2 3 4 5 6 7 RL1 −255 −114 −133 −116 −78 −38 5 117 RL3 174154 127 91 50 7 −38 −133The location of the primary read level with respect to table 2 isbetween bin 3 and bin 4. A table generated for LSB page may only requireone row, as shown in Table 3:

TABLE 3 0 1 2 3 4 5 6 7 RL2 −255 −199 −163 −119 −70 −23 24 110

As described previously, offsets (or bias values) may be implemented inconnection with primary read levels (e.g., RL1, RL2, RL3) in order toobtain an optimal read level having a low bit error rate. Offset valuesmay be set globally, e.g., for a die or block, or on an individualwordline basis. Each wordline may have different and/or uniquecharacteristics that cause each wordline to exhibit greater or lessererrors during read operations. Accordingly, in order to obtain the besterror rate—the minimum error rate—the optimum read level must bedetermined. In some aspects, optimal read levels for a wordline may bedetermined by lab data. In various examples described herein, thewordline may be read at different offsets and the error count for eachread placed in a table for later comparison. While this lab data may beuseful for a portion of the lifecycle of the memory, characteristics ofmemory cells change over time and the data may not be as useful inobtaining the best error rates after a period of time in the life cycleof the memory cells.

Different tables 400, e.g., may be stored in flash memory for each readlevel (e.g., RL1, RL2, or RL3) and for multiple different periods in theexpected life of the flash memory so that a device may obtain nearoptimal bit error rates throughout the expected life of the device.However, the lab data may not apply to every die, every block, or evenevery form of degradation that may be experience by the individualwordlines or flash memory cells over the life of the device.Accordingly, the subject technology provides a mechanism for dynamically(e.g., at run time) calibrating read levels by estimating new readoptimum read levels and/or offsets during operation of the flash memorydevice.

FIG. 10A to 10C depict example linear interpolation graphs forcalibrating example read levels and/or read level offsets, according tovarious aspects of the subject technology. The graphs are representativeof how an algorithm of the subject technology determines a newcalibrated offset for read operations. With reference to tables 2 and 3,above, each graph charts a calculated LLR value with respect topredetermined offset values associated with each bin. Accordingly, thex-axis represents a range of negative and positive offset values from anun-calibrated, zero offset 1002. In the depicted example, un-calibratedoffset 1002 (marked as “0”) corresponds to the respective “center” readlevel (e.g., RL1, RL2, or RL3) used to initially determine theprogrammed level of a memory cells, before it is reread by the“supplemental” read levels used to generate the bins.

Each bin spans 6 ticks on the x axis, according to a fixed amount. Inthe depicted example, offsets are evenly spaced 6 ticks apart. Offsets 0to +6 on the x-axis correspond to bin 4, offsets +7 to +12 correspond tobin 5, offsets +13 to +18 correspond to bin 6, and offsets +19 to +24correspond to bin 7. Similarly, offsets 0 to −6 on the x-axis correspondto bin 3, offsets −7 to −12 correspond to bin 2, offsets −13 to −18correspond to bin 2, and offsets −19 to −24 correspond to bin 0. Thecorresponding LLR values placed in the bins are charted at offset values−21, −15, −9, −3, +3, +9, +15, and +21, respectively. These offsetvalues are merely provided as examples and other offset values may beused, according to the particular memory implementation.

Once the memory cells of a wordline or block are read, and LLRsdetermined, the subject technology assigns the LLRs to bins for each ofRL1, RL2, and RL3 in a table, as shown in Tables 2 and 3, above. Linearinterpolation of the LLR values across the corresponding bins (e.g.,0-7) is then used to determine a zero crossing point (1004) of therepresented LLR values. The zero crossing point is an estimate of thepoint at which the conditional probability distributions associated withthe threshold voltage of the cell are equal, and representative of theread level that minimizes the bit error rate. Interpolation increasesthe accuracy of the estimated zero crossing point without the need foradditional reads.

In this regard, the LLR values in a row of the table are scanned todetermine where the zero crossing point is. With regard to FIG. 10A andTable 1, above, the zero crossing point (1004) for RL1 is between bin 5and bin 6, having LLR values −38 and 5, respectively. An offset value(1006) along the x-axis corresponding to the zero crossing point (1004)is selected as the calibrated offset value for the corresponding readlevel (e.g., RL1, RL2, or RL3). In FIG. 10A, the calibrated offset valueis determined to be approximately +14 ticks (e.g., +175 mV, with everytwo ticks being 25 mV). In FIG. 10B, the calibrated offset value isdetermined to be approximately +12 ticks. In FIG. 10C, the calibratedoffset value is determined to be approximately +10 ticks.

A calibrated offset value may be determined for each read level (e.g.,RL1, RL2, or RL3), as indicated above. In some implementations, thecalibrated offset values may replace or be used to adjust existingoffset values for individual wordlines, or globally for a block ordie(s). In some implementations, the calibrated offset voltage replacesa read level offset previously associated with an offset wordline groupdetermined by, for example, processes 700 and/or 800. In some aspects,the previously associated read level offset will be adjusted by thecalibrated voltage.

The calibrated offset voltages need not be determined for all memorycells of a block, die, or group but, rather, may be determined for oneor more selected wordlines, portions of a wordline, one or morecodewords, and the like. In some implementations, the calibrated offsetvalues may be stored in addition to the offsets determined for awordline group, and summed at the time of a read operation with theoffset assigned to the wordline group and any global offset, ifavailable.

Read levels may be calibrated using the above procedure at specificpoints in the expected lifetime of a flash device. For example, thecalibration procedure may be executed when a block becomes subject to apredetermined number of program/erase cycles. The calibration proceduremay be executed in a “heroic mode,” e.g., in response to an error countproduced in connection with a read operation satisfying a predeterminedthreshold number of errors. The predetermined threshold may be withrespect to one or more codewords, wordlines, blocks or combinationthereof, for a single read operation or for multiple read operationsover a period of time. In some implementations, the predeterminedthreshold of errors may include the failure to read or decode one ormore memory cells that are subject of the read operation. For example,the number of errors produced may be more than the ECC scheme associatedwith the flash memory device can handle.

In response to identifying a wordline associated with an overly higherror count (satisfying the threshold), a flash controller or componentthereof implementing the subject technology may read memory cells in oneor more wordlines adjacent to the identified wordline to generate theLLR values for the respective bins, and determine a new calibratedoffset value for the reading the wordlines using the foregoing LLRlinear interpolation process. If the adjacent wordlines can be read andsuccessfully decoded then the new calibrated offset value may be used inan attempt to recover a read of memory cells in the identified wordline.The identified wordline may then be re-read using the read level set to(e.g., adjusted by) the calibrated offset value.

Similarly, a codeword (e.g., spanning wordlines, or a portion of awordline) subject to a read operation may be identified as having anerror rate that satisfies an error threshold. For example, all attemptsto decode the codeword may have failed. In response to identifying thecodeword, the flash controller or component thereof implementing thesubject technology may read memory cells in one or more other codewordsadjacent to the identified codeword to generate the LLR values, anddetermine the new calibrated offset value using the foregoing LLR linearinterpolation process. For example, current LLR values may not beoptimized to decode the identified codeword. An adjacent codeword maythen read to find an improved set of LLR values. If the adjacentcodewords can be read and successfully decoded (and new LLR valuesgenerated) then the new calibrated offset value may be used in anattempt to recover the failed codeword. The identified codeword may thenbe re-read using the read level set to (e.g., adjusted by) thecalibrated offset value.

TABLE 4 0 1 2 3 4 5 6 7 RL1 −255 −108 −71 −25 −22 −70 111 146 RL2 −255−123 −74 −24 −26 −74 109 119 RL3 191 112 70 23 −26 −74 −117 −165

Table 4, above, is representative of updated LLR values for each bin,after calibration of the respective read level offsets corresponding tothe LLR values of Tables 2 and 3. As may be seen by Table 4, the zerocrossing point (1004) is now between bins 3 and 4 for all three readlevels. FIGS. 10D to 10F depict example linear interpolation graphs forre-calibrating example read levels and/or read level offsets, accordingto various aspects of the subject technology. After the read levels havebeen adjusted according to the process described above with respect toFIGS. 10A to 10C, the adjusted read level(s) may then be recalibrated toverify or finetune the calibration, using the same process. Theresulting LLR values are expected to eventually converge to a zerooffset, as shown by Table 4 and the graphs of FIGS. 10D to 10F.

FIGS. 11A and 11B depict example read level optimization modes,according to various aspects of the subject technology. Flash memoryarchitecture may be configured such that data is stored and retrievedvia multiple channels 1102 of memory, with each channel 1102, e.g.,including one or more memory blocks 1104. Each memory block 1104addressable by each channel 1102 is further addressable by pageaddresses 1106. In the depicted examples, each channel addresses asingle memory block, with each memory block having 256 pages (e.g.,pages 0-255). As described previously, a page 1106 may be physicallyrepresented by a wordline and thus the term page and wordline may beused interchangeably.

In some implementations, as depicted by FIG. 11A, an offset voltage maybe assigned globally, e.g., to all blocks and all pages addressable bythe memory channels. In this implementation, the same offset value is a“global” offset used when reading memory cells of any page or blockassociated with the plurality of memory channels. Accordingly, theglobal offset may be calibrated using any of the techniques describedherein. In some implementations, as depicted by FIG. 11B, multipleoffsets may be used, with each offset value being associated with eachpage (wordline), e.g., by associating each offset value with a pageaddress 1106. Associations 1110 may be generated between offset valuesand page such that the same offset value is used for each page acrossall of the memory channels. These “page offsets” may be relative toglobal offsets, in that a global offset will be applied (and adjusted asneeded) to all pages, and the global offsets will be modified by thecorresponding page offsets as each page is read.

FIG. 12 depicts a flow diagram of an example process 1200 forcalibrating read levels for reading a plurality of memory cells in astorage device, according to various aspects of the subject technology.For explanatory purposes, the various blocks of example process 1200 aredescribed herein with reference to the components and/or processesdescribed herein. The one or more of the blocks of process 1200 may beimplemented, for example, by one or more processors, including, forexample, flash memory controller 1501 of FIG. 15 or one or morecomponents or processors of controller 1501. In some implementations,one or more of the blocks may be implemented apart from other blocks,and by one or more different processors or controllers. Further forexplanatory purposes, the blocks of example process 1200 are describedas occurring in serial, or linearly. However, multiple blocks of exampleprocess 1200 may occur in parallel. In addition, the blocks of exampleprocess 1200 need not be performed in the order shown and/or one or moreof the blocks of example process 1200 need not be performed.

According to various implementations, the blocks of process 1200correspond to, or supplement the process described with respect to FIG.9 and FIGS. 10A to 10F. The blocks of process 1200, or subset thereof,may be executed for each possible read level used in a flash memorydevice. For example, the blocks of process 1200 may be executed togenerate, adjust, and/or calibrate offsets for wordlines or wordlinegroups for RL1, RL2, and RL3. In various aspects, offset wordline groupsof different sizes and/or having different offset value pairings may begenerated for each different read level. Additionally, the blocks ofprocess 1200 may be executed to generate, adjust, and/or calibrateoffsets for different groups for different blocks, and or die. Process1200 may be implemented during configuration of a storage device, priorto or during operation.

In the depicted example, a flash memory device provides a read levelvoltage sufficient to read memory cells that are programmed to aprogramming level (1202). For example, the read level voltage may bepre-programmed into a state machine of flash memory device by themanufacturer or the storage device controller. As described previously,the memory cells may be a single level or multi-level non-volatilememory cells configured to be programmed to one of four programminglevels. For example, with reference to FIG. 2B, L0 and L3 programminglevels may be associated with first bit values (e.g., representative ofa binary 0 or 1 of a most significant bit) and L1 and L2 programminglevels may be associated with the second bit values (e.g.,representative of a binary 0 or 1 of a least significant bit). Asdescribed previously, when voltage is applied to a memory cell at aparticular read level (e.g., RL1, RL2, RL3) corresponding to the programlevel of the cell the cell will conduct indicating the program level.

After a predetermined period of time in a life cycle of the flash memorydevice (e.g., after 30,000 program/erase cycles), reliability valuescorresponding to a plurality of reads of one or more of the memory cellsare generated (1204). In this example, each of the reads uses avariation of the read level voltage, and each generated reliabilityvalue is indicative of a likelihood that an output state of the memorycells is equal to a one of multiple predetermined programmed states,with a range of the reliability values spanning negative and positivevalues. As described previously, for the plurality of reliabilityvalues, a positive reliability value may be indicative of acorresponding output state being a binary 0, and a negative reliabilityvalue may be indicative of the corresponding output state being a binary1.

After the reliability values are generated, an offset voltage isidentified, offset from the read level voltage (1206). In the depictedexamples of FIGS. 10A to 10C, the offset corresponds to a zero crossingpoint 1004 in the range of the reliability values (e.g., of Tables 2and/or 3).

After the offset voltage is identified (e.g., for the read level) theread level voltage is set to a calibrated voltage based on the offsetvoltage (1208). According to various aspects of the subject technology,setting the read level voltage to the calibrated voltage may include,e.g., in connection with a read operation, retrieving the identifiedoffset voltage from a stored location, and adjusting the read levelvoltage by the identified offset voltage to read the memory cells. Insome implementations, the read operation is performed on memory cellsacross a plurality of memory channels, each channel being configured toaddress one or more memory blocks.

With reference to FIG. 11A, the identified offset voltage may beassociated with all blocks and all pages addressable by the plurality ofmemory channels so that the read level is adjusted by the identifiedoffset voltage when reading memory cells of any page or block associatedwith the plurality of memory channels. With reference to FIG. 11B, theidentified offset voltage may be associated with a page address, and theread level adjusted by the identified offset voltage when reading memorycells associated with the page address via any of the plurality ofmemory channels, with each page address addressable via the plurality ofmemory channels being associated with a different offset voltage.

Additionally, the process of calibration may be applied to updateoffsets for individual wordlines or to update offsets associated withoptimal wordline groups. For example, a plurality of predetermined readlevel offsets may be stored, with each predetermined read level offsetbeing associated with a group of wordlines for use with a respectiveread level voltage in reading memory cells in the group. For arespective group of wordlines, the read level offset previouslyassociated with the group may be updated with the identified offsetvoltage. Accordingly, in connection with a read operation, the updatedread level offset may be retrieved from its stored location (e.g., alookup table) to set the read level voltage to the calibrated voltage,and the newly calibrated voltage used to read the respective group ofwordlines.

FIG. 13 depicts a flow diagram of an example process 1300 forcalibrating read levels to recover data, according to various aspects ofthe subject technology. The foregoing calibration process 1200 mayfurther be applied to recover data that cannot be read or decoded. Inthe depicted example implementation of FIG. 13, during a read operation,one or more wordlines or codewords are identified as being associated anerror rate that satisfies (e.g., exceeds) an error threshold (1302). Forexample, reading a wordline or codeword may produce too many data errorsfor the error correction coding to handle. In this regard, the readoperation may not be able to read the data stored at the one or moreidentified wordlines.

In response to identifying the wordline(s) or codeword(s), process 1200of FIG. 12, or one or more blocks thereof, may be invoked to recoverdata from the one or more wordlines. In this regard, memory cells in oneor more wordlines or codewords adjacent to the identified wordline(s) orcodeword(s) are read to generate the plurality of reliability valuesdescribed above with respect to FIGS. 10A to 10C (1304). After thereliability values are generated, the new calibrated offset voltage isidentified (e.g., that corresponds to a zero crossing point 1004 in therange of the reliability values) and the read level voltage isset/adjusted to the new calibrated offset voltage (1306). The identifiedwordline(s) or codeword(s) are then re-read using the newly calibratedread level voltage (1308).

Regenerating Read Level Offset Groups

FIG. 14 depicts a flow diagram of an example process 1400 forregenerating a plurality of optimal offset wordline groups based onregenerating and reindexing a table of error counts, according tovarious aspects of the subject technology. For explanatory purposes, thevarious blocks of example process 1400 are described herein withreference to the components and/or processes described herein. One ormore of the blocks of process 1400 may be implemented, for example, byone or more processors, including, for example, flash memory controller1501 of FIG. 15 or one or more components or processors of controller1501. In some implementations, one or more of the blocks may beimplemented apart from other blocks, and by one or more differentprocessors or controllers. Further for explanatory purposes, the blocksof example process 1400 are described as occurring in serial, orlinearly. However, multiple blocks of example process 1400 may occur inparallel. In addition, the blocks of example process 1400 need not beperformed in the order shown and/or one or more of the blocks of exampleprocess 1400 need not be performed.

According to various implementations, one or more blocks of process 1400may correspond to, or supplement one or more blocks of processes 700,800, 1300, and/or 1200, and/or the processes described with respect toFIG. 9 and FIGS. 10A to 10F. For example, block 1402 may generate thetable of error counts used in block 712. Block 1404 may correspond tothe block 804 and/or blocks 708-720. The blocks of process 1400, orsubset thereof, may be executed for each possible read level used toread memory cells in a flash memory device. These memory cells areconfigured to be programmed to a plurality of programming levels, eachprogramming level being determined by reading the memory cells at arespective read level voltage. The blocks of process 1400 may beexecuted to generate, adjust, and/or calibrate offsets for wordlines orwordline groups for RL1, RL2, and RL3. A portion of the blocks ofprocess 1400 may be executed by algorithm 602. In various aspects,offset wordline groups of different sizes and/or having different offsetvalue pairings may be generated for each different read level.Additionally, the blocks of process 1400 may be executed to generate,adjust, and/or calibrate offsets for different groups for differentblocks, and or die. Process 1400 may be implemented during configurationof a data storage system, prior to or during operation.

In the depicted example, a system according to the subject technologygenerates a table of error counts based on reading a plurality ofwordlines of a memory block (1402). Table 400 is one example of a tableof error counts that may be generated by the subject technology. Asdescribed previously, to generate a new table, each wordline may be readmultiple times using a read level voltage modified by a different offsetvoltage. Each read may produce an error count for each offset voltage.The table is generated such that the rows of the table correspond towordlines and the columns correspond to offset values. The error countsthat are generated may then be indexed by wordline and respective offsetvoltages.

In connection with configuring a storage device implementing the subjecttechnology, a plurality of optimal offset wordline groups are generated(e.g., by algorithm 602) based on the table of error counts and aninitial division of the plurality of wordlines (1404). As describedpreviously with respect to processes 700 and 800 and FIGS. 7 and 8, eachoptimal offset wordline group may include a consecutively groupedportion of the wordlines paired with a corresponding offset voltage, thepairings selected for an overall lowest possible error count for readingwordlines in each of the offset wordline groups. In this regard, a tableof error counts may be indexed by respective wordlines and read leveloffset voltages to determine the maximum and/or minimum error countspossible for each of the wordlines. The wordlines may then be organizedinto consecutive groups, with each group paired with an offset valuethat provides the lowest overall possible error count degradation forthe groupings as compared to using offset values for each individualwordline.

After the optimal wordline groups (including corresponding offsetvoltages) are generated, the storage device is configured to performread operations on respective wordlines of a memory block using a readlevel offset voltage corresponding to the generated offset wordlinegroup that includes the respective wordlines (1406). Accordingly, inconnection with reading memory cells of a particular wordline of anoffset wordline group, the offset voltage associated with the respectiveoffset wordline group may be identified and the memory cells read usingthe identified offset voltage. In various implementations, theidentified offset voltage modifies the respective read level voltage toread the memory cells with fewer errors than if the respective readlevel voltage was not modified.

After a predetermined period of time in a life cycle of the memory block(e.g., after memory cells in the memory block having undergone 30,000program/erase cycles), the optimal wordline groups, including theirassociated offset values, may be recalibrated. In this regard, the tableof error counts is regenerated (1408). The table of error counts may bere-generated, for example, based on re-reading the plurality ofwordlines of a memory block, for example, under current conditions(e.g., voltage levels) of the flash memory device.

In some implementations, before the table of error counts isregenerated, the read levels and/or offset voltages used to generate thetable may be calibrated. With brief reference to FIG. 13 and process1300, reliability values corresponding to multiple reads about arespective read level voltage may be generated, an updated offsetvoltage for the read level voltage identified, and the storage deviceconfigured to re-read the plurality of wordlines of the memory blockusing the updated offset voltage in connection with the read levelvoltage. Accordingly, each of the reads may use a variation of the readlevel voltage, and each generated reliability value may be indicative ofa likelihood that an output state of the memory cells is equal to apredetermined programmed state (e.g., log-likelihood ratio). A range ofthe reliability values may span negative and positive values. Theidentified updated offset voltage used to re-read the wordlines maycorrespond to a zero crossing point in the range of the reliabilityvalues.

Once the table of error counts is regenerated, the optimal offsetwordline groups are regenerated based on indexing the re-generated tableof error counts by the wordlines and the read level offset voltages(1410). The optimal offset wordline groups may be regenerated in themanner described by one or more blocks of process 700 and/or process800.

Many of the above-described features of example processes 1200, 1300,and 1400 and related features and applications, may be implemented assoftware processes that are specified as a set of instructions recordedon a computer readable storage medium (also referred to as computerreadable medium). When these instructions are executed by one or moreprocessing unit(s) (e.g., one or more processors, cores of processors,or other processing units), they cause the processing unit(s) to performthe actions indicated in the instructions. Examples of computer readablemedia include, but are not limited to, CD-ROMs, flash drives, RAM chips,hard drives, EPROMs, etc. The computer readable media does not includecarrier waves and electronic signals passing wirelessly or over wiredconnections.

FIG. 15 is a block diagram depicting components of an example datastorage system 1500 (for example, a solid state drive) according tovarious implementations of the subject technology. Data storage system1500 may include a data storage controller 1501, storage medium 1502,and flash memory device 1503. Controller 1501 may use storage medium1502 for temporary storage of data and information used to manage datastorage system 1500. Controller 1501 may include several internalcomponents (not shown) such as one or more processors, a read-onlymemory, a flash component interface (for example, a multiplexer tomanage instruction and data transport along a serial connection to flashmemory device 1503), an I/O interface, error correction circuitry, andthe like. In some aspects, one or more elements of controller 1501 maybe integrated into a single chip. In other aspects, the elements may beimplemented on two or more discrete components.

Controller 1501, or one or more components therein, may be configured toexecute code or instructions to perform the operations and functionalitydescribed herein. For example, controller 1501 may be configured toperform operations for managing request flow and address mappings, andto perform calculations and generate commands. The processor ofcontroller 1501 may be to monitor and control the operation of thecomponents in data storage controller 1501. The processor may be ageneral-purpose microprocessor, a microcontroller, a digital signalprocessor (DSP), an application specific integrated circuit (ASIC), afield programmable gate array (FPGA), a programmable logic device (PLD),a controller, a state machine, gated logic, discrete hardwarecomponents, or a combination of the foregoing. One or more sequences ofinstructions may be stored as firmware on ROM within controller 1501and/or its processor. One or more sequences of instructions may besoftware stored and read from storage medium 1502, flash memory device1503, or received from host device 1510 (for example, via a hostinterface). ROM, storage medium 1502, flash memory device 1503,represent examples of machine or computer readable media on whichinstructions/code executable by controller 1501 and/or its processor maybe stored. Machine or computer readable media may generally refer to anytangible and/or non-transitory medium or media used to provideinstructions to controller 1501 and/or its processor, including bothvolatile media, such as dynamic memory used for storage media 1502 orfor buffers within controller 1501, and non-volatile media, such aselectronic media, optical media, and magnetic media.

Accordingly, data storage system 1500 may further include a hostinterface 1505. Host interface 1505 is configured to be coupled to hostdevice 1510, to receive data from and send data to host device 1510.Host interface 1505 may include both electrical and physical connectionsfor operably coupling host device 1510 to controller 1501. Hostinterface 1505 is configured to communicate data, addresses, and controlsignals between host device 1510 and controller 1501. In this manner,controller 1501 is configured to store data received from host device1510 in flash memory device 1503 in response to a write command fromhost device 1510, and to read data stored in flash memory device 1503and to transfer the read data to host device 1510 via host interface1505 in response to a read command from host device 1510.

Host device 1510 represents any device configured to be coupled to datastorage system 1500 and to store data in data storage system 1500. Hostdevice 1510 may be a computing system such as a personal computer, aserver, a workstation, a laptop computer, PDA, smart phone, and thelike. Alternatively, host device 1510 may be an electronic device suchas a digital camera, a digital audio player, a digital video recorder,and the like.

In some aspects, storage medium 1502 represents volatile memory used totemporarily store data and information used to manage data storagesystem 1500. According to one aspect of the present disclosure, storagemedium 1502 is random access memory (RAM) such as double data rate (DDR)RAM. Other types of RAM also may be used to implement storage medium1502. Storage medium 1502 may be implemented using a single RAM moduleor multiple RAM modules. While storage medium 1502 is depicted as beingdistinct from controller 1501, those skilled in the art will recognizethat storage medium 1502 may be incorporated into controller 1501without departing from the scope of the present disclosure.Alternatively, storage medium 1502 may be a non-volatile memory such asa magnetic disk, flash memory, peripheral SSD, and the like.

As further depicted in FIG. 2, data storage system 1500 may also includea bus. The bus may use suitable interfaces standard including, but notlimited to, Serial Advanced Technology Attachment (SATA), AdvancedTechnology Attachment (ATA), Small Computer System Interface (SCSI),PCI-extended (PCI-X), Fibre Channel, Serial Attached SCSI (SAS), SecureDigital (SD), Embedded Multi-Media Card (EMMC), Universal Flash Storage(UFS) and Peripheral Component Interconnect Express (PCIe).

Host device 1510 and data storage system 1500 may be in communicationwith each other via a wired or wireless connection and may be local toor remote from one another. According to some aspects, data storagesystem 1500 may include pins (or a socket) to mate with a correspondingsocket (or pins) on host device 1510 to establish an electrical andphysical connection. According to one or more other aspects, datastorage system 1500 includes a wireless transceiver to place host device1510 and data storage system 1500 in wireless communication with eachother.

Flash memory device 1503 represents a non-volatile memory device forstoring data. According to one aspect of the present disclosure, flashmemory device 1503 includes, for example, a NAND flash memory. Flashmemory device 1503 may include a single flash memory device or chip, andmay include multiple flash memory devices or chips arranged in multiplechannels. Flash memory device 1503 is not limited to any particularcapacity or configuration. For example, the number of physical blocks,the number of physical pages per physical block, the number of sectorsper physical page, and the size of the sectors may vary within the scopeof the present disclosure.

Flash memory may have a standard interface specification. This standardensures that chips from multiple manufacturers may be usedinterchangeably (at least to a large degree). The interface may furtherhide the inner working of the flash memory and return only internallydetected bit values for data.

The term “software” is meant to include, where appropriate, firmwareresiding in read-only memory or applications stored in magnetic storage,which can be read into memory for processing by a processor. Also, insome implementations, multiple software aspects of the subjectdisclosure can be implemented as sub-parts of a larger program whileremaining distinct software aspects of the subject disclosure. In someimplementations, multiple software aspects can also be implemented asseparate programs. Finally, any combination of separate programs thattogether implement a software aspect described here is within the scopeof the subject disclosure. In some implementations, the softwareprograms, when installed to operate on one or more electronic systems,define one or more specific machine implementations that execute andperform the operations of the software programs.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, object, orother unit suitable for use in a computing environment. A computerprogram may, but need not, correspond to a file in a file system. Aprogram can be stored in a portion of a file that holds other programsor data (e.g., one or more scripts stored in a markup languagedocument), in a single file dedicated to the program in question, or inmultiple coordinated files (e.g., files that store one or more modules,sub programs, or portions of code). A computer program can be deployedto be executed on one computer or on multiple computers that are locatedat one site or distributed across multiple sites and interconnected by acommunication network.

It is understood that illustrative blocks, modules, elements,components, methods, and algorithms described herein may be implementedas electronic hardware, computer software, or combinations of both. Toillustrate this interchangeability of hardware and software, variousillustrative blocks, modules, elements, components, methods, andalgorithms have been described above generally in terms of theirfunctionality. Whether such functionality is implemented as hardware orsoftware depends upon the particular application and design constraintsimposed on the overall system. Skilled artisans may implement thedescribed functionality in varying ways for each particular application.Various components and blocks may be arranged differently (e.g.,arranged in a different order, or partitioned in a different way) allwithout departing from the scope of the present disclosure.

It is understood that the specific order or hierarchy of steps in theprocesses disclosed is presented as an illustration of some exemplaryapproaches. Based upon design preferences and/or other considerations,it is understood that the specific order or hierarchy of steps in theprocesses may be rearranged. For example, in some implementations someof the steps may be performed simultaneously. Thus the accompanyingmethod claims present elements of the various steps in a sample order,and are not meant to be limited to the specific order or hierarchypresented.

The previous description is provided to enable any person skilled in theart to practice the various aspects described herein. The previousdescription provides various examples of the present disclosure, and thepresent disclosure is not limited to these examples. Variousmodifications to these aspects will be readily apparent to those skilledin the art, and the generic principles defined herein may be applied toother aspects. Thus, the claims are not intended to be limited to theaspects shown herein, but is to be accorded the full scope consistentwith the language claims, wherein reference to an element in thesingular is not intended to mean “one and only one” unless specificallyso stated, but rather “one or more.” Unless specifically statedotherwise, the term “some” refers to one or more. Pronouns in themasculine (e.g., his) include the feminine and neuter gender (e.g., herand its) and vice versa. Headings and subheadings, if any, are used forconvenience only and do not limit the subject disclosure.

The predicate words “configured to”, “operable to”, and “programmed to”do not imply any particular tangible or intangible modification of asubject, but, rather, are intended to be used interchangeably. Forexample, a processor configured to monitor and control an operation or acomponent may also mean the processor being programmed to monitor andcontrol the operation or the processor being operable to monitor andcontrol the operation. Likewise, a processor configured to execute codemay be construed as a processor programmed to execute code or operableto execute code.

The phrases “in communication with” and “coupled” mean in directcommunication with or in indirect communication with via one or morecomponents named or unnamed herein (e.g., a memory card reader)

A phrase such as an “aspect” does not imply that such aspect isessential to the present disclosure or that such aspect applies to allconfigurations of the present disclosure. A disclosure relating to anaspect may apply to all configurations, or one or more configurations.An aspect may provide one or more examples. A phrase such as an aspectmay refer to one or more aspects and vice versa. A phrase such as an“embodiment” does not imply that such embodiment is essential to thepresent disclosure or that such embodiment applies to all configurationsof the present disclosure. A disclosure relating to an implementationmay apply to all aspects, or one or more aspects. An implementation mayprovide one or more examples. A phrase such as an “embodiment” may referto one or more implementations and vice versa. A phrase such as a“configuration” does not imply that such configuration is essential tothe present disclosure or that such configuration applies to allconfigurations of the present disclosure. A disclosure relating to aconfiguration may apply to all configurations, or one or moreconfigurations. A configuration may provide one or more examples. Aphrase such as a “configuration” may refer to one or more configurationsand vice versa.

The word “exemplary” is used herein to mean “serving as an example orillustration.” Any aspect or design described herein as “exemplary” isnot necessarily to be construed as preferred or advantageous over otheraspects or designs.

What is claimed is:
 1. A machine-implemented method of reading aplurality of flash memory cells in a storage device, the methodcomprising: dividing a plurality of flash memory wordlines of a flashstorage device into a plurality of wordline groups based on read errorcounts associated with the wordlines and a plurality of read leveloffsets; associating each wordline group with one of a plurality of readlevel offsets determined while dividing the plurality of flash memorywordlines; and storing associations between the plurality of read leveloffsets and the plurality of wordline groups for use in connection withread levels to read the flash memory wordlines of the respectivewordline groups.
 2. The machine-implemented method of claim 1, whereineach of the plurality of wordline groups comprises consecutively orderedwordlines of a flash memory block.
 3. The machine-implemented method ofclaim 1, wherein dividing the plurality of flash memory wordlines intothe plurality of wordline groups comprises: selecting respectivepermutations of consecutive wordline subgroups from within apredetermined set of wordline candidate groups based on a minimum oftotal error counts associated with the respective permutations, theconsecutive wordline subgroups each being associated with a read leveloffset corresponding to a minimum of error counts associated with aplurality of possible read level offsets.
 4. The machine-implementedmethod of claim 3, wherein dividing the plurality of flash memorywordlines into the plurality of wordline groups comprises: (a) selectingfirst and second consecutive candidate wordline groups from thepredetermined set of candidate wordline groups; (b) providing aplurality of subgroup permutations for the selected first and secondconsecutive candidate wordline groups, each subgroup permutationcomprising multiple consecutive wordline subgroups of wordlines spanningthe first and second consecutive wordline groups; (c) for each wordlinesubgroup of a respective subgroup permutation, identifying from theplurality of possible read level offsets a respective read level offsetthat when used with the read level to read the wordlines in the wordlinesubgroup generates the least number of errors for the wordline subgroup;and (d) choosing one of the plurality of subgroup permutations having alowest total error count for consecutive wordline subgroups in thesubgroup permutation based on the identified read level offsets for theconsecutive wordline subgroups, wherein the plurality of wordline groupsare based at least in part on one or more read level offsetscorresponding to the selected one of the plurality of subgrouppermutations.
 5. The machine-implemented method of claim 4, whereindividing the plurality of flash memory wordlines into the plurality ofwordline groups further comprises: (e) storing an association between afirst of the consecutive wordline subgroups in the chosen subgrouppermutation and a corresponding identified read level offset; and (f)repeating steps (a) through (e) using a second of the consecutivewordline subgroups in the chosen subgroup permutation as the firstconsecutive candidate wordline group and a next candidate group from thepredetermined set of candidate wordline groups as the second consecutivecandidate wordline group, the repeating ending when associations havebeen stored for all wordlines in the predetermined set of candidatewordline groups.
 6. The machine-implemented method of claim 5, whereindividing the plurality of flash memory wordlines into the plurality ofwordline groups further comprises: repeating steps (a) through (f) untilwordline boundaries of the consecutive wordline subgroups do not changefrom one iteration to a next iteration, or until an overall bit errorrate measured based on identified read level offsets for the consecutivewordline subgroups does not change from one iteration to a nextiteration, or a certain number of iterations is reached.
 7. Themachine-implemented method of claim 3, wherein each consecutive wordlinesubgroup of a respective permutation is generated based on aninterleaving of consecutive wordlines within the predetermined set ofcandidate wordline groups.
 8. The machine-implemented method of claim 1,wherein dividing the plurality of flash memory wordlines into theplurality of wordline groups comprises: selecting respectivepermutations of consecutive wordline subgroups from within apredetermined set of candidate groups based on selecting a minimum ofmaximum error counts associated with the respective permutations, theconsecutive wordline subgroups each being associated with a read leveloffset corresponding to a minimum of respective error counts associatedwith a plurality of possible read level offsets.
 9. Themachine-implemented method of claim 8, wherein dividing the plurality offlash memory wordlines into the plurality of wordline groups comprises:(a) selecting first and second consecutive candidate wordline groupsfrom the predetermined set of candidate wordline groups; (b) providing aplurality of subgroup permutations for the selected first and secondconsecutive candidate wordline groups, each subgroup permutationcomprising multiple consecutive wordline subgroups of wordlines spanningthe first and second consecutive wordline groups; (c) for eachconsecutive wordline subgroup of a respective subgroup permutation,determining a maximum error count associated with reading wordlines inthe wordline subgroup for each possible read level offset used with theread level to read the wordlines of the wordline subgroup, and selectingfrom the plurality of possible read level offsets a read level offsetcorresponding to the minimum of the determined maximum error counts forthe wordline subgroup; (d) for each subgroup permutation, determining amaximum error count of the error counts associated with the wordlinesubgroups of the subgroup permutation; and (e) choosing one of theplurality of subgroup permutations having a minimum of the determinedmaximum error counts.
 10. The machine-implemented method of claim 9,wherein dividing the plurality of flash memory wordlines into theplurality of wordline groups further comprises: (f) storing anassociation between a first of the consecutive wordline subgroups in thechosen subgroup permutation and a corresponding identified read leveloffset; and (g) repeating steps (a) through (f) using a second of theconsecutive wordline subgroups in the chosen subgroup permutation as thefirst consecutive candidate wordline group and a next candidate groupfrom the predetermined set of candidate wordline groups as the secondconsecutive candidate wordline group, the repeating ending whenassociations have been stored for all wordlines in the predetermined setof candidate wordline groups.
 11. The machine-implemented method ofclaim 10, wherein dividing the plurality of flash memory wordlines intothe plurality of wordline groups further comprises: repeating steps (a)through (g) until wordline boundaries of the consecutive wordlinesubgroups do not change from one iteration to a next iteration, or untilan overall bit error rate measured for the consecutive wordlinesubgroups does not change from one iteration to a next iteration, or acertain number of iterations is reached.
 12. The machine-implementedmethod of claim 3, further comprising: generating an error count table,each error count in the table being indexed based on a respective readlevel offset and a respective flash memory wordline; and generating arespective normalized read level offset group based on: indexing theerror count table by a plurality of consecutive flash memory wordlinesto identify corresponding read level offsets having a lowest error countfor each consecutive flash memory wordline, and determining a group ofthe consecutive flash memory wordlines that when associated with asingle identified offset have a minimum possible error count for thegroup of the consecutive flash memory wordlines.
 13. Themachine-implemented method of claim 1, wherein the read level is avoltage to read flash memory cells that are programmed to a programminglevel.
 14. The machine-implemented method of claim 1, wherein eachmemory cell of the flash memory block is configured to be programmed toone of a plurality of possible programming levels, with each levelcapable of being determined by a respective read level, and wherein arespective plurality of wordline groups is generated and stored for eachrespective read level.
 15. The machine-implemented method of claim 1,wherein each read level offset is a voltage bias that, when summed witha corresponding read level, reduces the amount of errors produced from aread operation performed on a group of flash memory cells.
 16. Themachine-implemented method of claim 1, wherein each flash memorywordline comprises flash memory cells programmed with one or more pagesof data.
 17. The machine-implemented method of claim 1, furthercomprising: configuring the storage device to retrieve a read leveloffset for a read operation based on a respective read level being usedin the read operation and an address of a wordline that is the subjectof the read operation being associated with a flash memory wordlinegroup associated with the read level offset.
 18. The machine-implementedmethod of claim 1, wherein the plurality of read level offsets arestored by the storage device in a lookup table.
 19. Amachine-implemented method, comprising: dividing a plurality of flashmemory wordlines into a plurality of wordline group offset pairs, eachpair comprising an offset voltage for a group of consecutive wordlinesin a flash memory block; and storing the plurality of wordline groupoffset pairs for use in connection with a read level in reading thememory cells during operation of the storage device.
 20. Themachine-implemented method of claim 19, wherein dividing the pluralityof wordlines comprises: selecting respective permutations of consecutivewordline subgroups from within a predetermined set of wordline candidategroups based on a minimum of total error counts associated with therespective permutations, the consecutive wordline subgroups each beingassociated with a read level offset corresponding to a minimum of errorcounts associated with a plurality of possible read level offsets. 21.The machine-implemented method of claim 19, wherein dividing theplurality of wordlines comprises: selecting respective permutations ofconsecutive wordline subgroups from within a predetermined set ofcandidate groups based on selecting a minimum of maximum error countsassociated with the respective permutations, the consecutive wordlinesubgroups each being associated with a read level offset correspondingto a minimum of maximum error counts associated with a plurality ofpossible read level offsets.
 22. A data storage system, comprising: aplurality of flash memory devices, each flash memory device comprising aplurality of flash memory blocks; and a controller coupled to theplurality of flash memory devices, wherein the controller is configuredto: store a plurality of wordline group offset pairs for use inconnection with a read level voltage in reading flash memory cellsduring a read operation, the wordline group offset pairs being formedfrom a division of a plurality of flash memory wordlines, wherein eachpair comprises an offset voltage for a group of consecutive wordlines ina flash memory block.
 23. The data storage system of claim 22, whereineach offset voltage is a voltage bias that, when summed with acorresponding read level voltage, reduces the amount of errors producedfrom the read operation.
 24. The data storage system of claim 22,wherein the wordline group offset pairs are stored in a lookup table.